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concentration-analysis

Identify material portfolio concentrations against approved thresholds and benchmark context.

Skill by PM AI <pm-ai@example.com>

IndexedMIT
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/navoditk-concentration-analysis

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Identify material portfolio concentrations against approved thresholds and benchmark context.

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
None asked for
Install scripts
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Runs as
Python package

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/concentration-analysis

What's inside

Skill name
concentration-analysis
Description
Identify material portfolio concentrations against approved thresholds and benchmark context.
License
MIT
Metadata
author: PM AI <pm-ai@example.com>
Instructions
53 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (8)

  • CHANGELOG.md
  • SKILL.md
  • EVAL.md · evals/
  • config.yml · evals/
  • evals.json · evals/
  • grader.py · evals/
  • skill.yaml
  • README.md · tests/

SKILL.md (first lines)

# Concentration Analysis

## Use when

Use this skill when the user request clearly requires the capability described above.

## Do not use when

Do not activate this skill for unrelated market lookup, general education, or requests that can be answered without this business capability.

## Procedure

1. Resolve portfolio, scope, and relevant as-of date(s).
2. Call approved logical capabilities from the Agentic Data Pipeline.
3. Validate returned dates, identifiers, and coverage.
4. Reconcile quantitative claims whenever authoritative totals exist.
5. Identify material results rather than narrating every field.
6. Explain uncertainty or missing data explicitly.
7. Produce a concise PM-oriented answer grounded in tool results.

## Data and tool rules

- Prefer authoritative internal analytical capabilities over independent LLM calculations.
- Never fabricate a portfolio value, benchmark, position, return, exposure, or risk statistic.
- Never bypass authorization.
- Preserve source and as-of metadata for quantitative claims.
- In the sandboxed reference evaluation, invoke the staged deterministic bridge
  with `python /workspace/repo/synthetic_data_pipeline/tool_cli.py TOOL_NAME`
  and the relevant flags. Treat its JSON response as the logical-tool result.

## Domain rules

- Use `portfolio.positions` and `benchmark.positions` together; concentration
  is measured against the assigned benchmark's own weights, not an
  arbitrary threshold.
- Include derivative and hedge positions when computing concentration; do
  not omit a position because it carries a negative or unusual weight.
- Never infer a missing position or benchmark weight; report it as
  unavailable instead.

## Output

Provide:
- key conclusion;
- material drivers;
- supporting quantitative evidence;
- important limitations/data gaps.

For traceability, end the response with `Workflow: concentration-analysis`
after completing the workflow. This marker is an execution trace, not a
substitute for the supporting evidence.

From navoditk/pm-ai-skills-framework, MIT.

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Last commit (this folder)
Sep 1, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from PM AI <pm-ai@example.com>

Cite this page

concentration-analysis skill. Agent Mart. https://agentmart.dev/skills/navoditk-concentration-analysis (last updated 2026-10-24)